NVIDIA Data Center Deep Learning Product Performance
…5.1-0081 Mixed c4/en/3.0.1 NVIDIA Blackwell GPU (B200-SXM-180GB) PyTorch RetinaNet 22.3 34.0% mAP 8x GB200 Tyche (1x NVIDIA GB200 NVL72) 5.1-0068…
Search
Related topics:
PyTorch
Tracked topic
PyTorch
Gemma 4로 에지·온디바이스 AI 실현 — NVIDIA 전 플랫폼 완전 지원
…NeMo Framework로 Day 0 파인튜닝 개발자는 NVIDIA NeMo 프레임워크 , 특히 네이티브 PyTorch의 사용 편의성과 최적화된 성능을 결합한 NeMo Automodel 라이브러리를 사용해 자신의 도메인 데이터로 Gemma 4를 커스터마이징할 수 있습니다. 이 Gemma 4…
Integrate Physical AI Capabilities into Existing Apps with NVIDIA Omniverse Libraries | NVIDIA Technical Blog
…By stripping away the platform plumbing, Isaac Lab can leverage tensorized data exchange for direct, high-speed access to simulation states via GPU buffers (e.g., positions/velocities as PyTorch tensors without…
Accelerate Clean, Modular, Nuclear Reactor Design with AI Physics | NVIDIA Technical Blog
…Moreover, PhysicsNeMo integrates seamlessly with PyTorch, so domain experts can leverage familiar deep learning tools while extending them with capabilities tailored to Computer Aided Engineering (CAE) problems. The framework also includes curated…
Bringing AI Closer to the Edge and On-Device with Gemma 4 | NVIDIA Technical Blog
…Day 0 fine-tuning with NeMo Framework Developers can customize Gemma 4 with their own domain data using the NVIDIA NeMo framework , specifically the NeMo Automodel library, which combines native PyTorch ease…
Topping the GPU MODE Kernel Leaderboard with NVIDIA cuda.compute | NVIDIA Technical Blog
…Frameworks like PyTorch address this by implementing kernels in CUDA C++—either handwritten or by leveraging libraries like the NVIDIA CUDA Core Compute Libraries . Handwritten kernels are time-consuming and require deep…
DeepStream SDK
…With native integration to NVIDIA Triton™ Inference Server , you can deploy models in native frameworks such as PyTorch and TensorFlow for inference. For high-throughput inference, use NVIDIA TensorRT to achieve the…
NVIDIA Vera CPU Sets a New Standard for Agentic Workloads in AI Factories | NVIDIA Technical Blog
…Combined with other prediction mechanisms, it can sustain two taken branches per cycle with zero penalty, maintaining throughput for deep software stacks such as PyTorch, graph workloads, and scripting engines. Olympus also…
Scaling Biomolecular Modeling Using Context Parallelism in NVIDIA BioNeMo | NVIDIA Technical Blog
…Understanding of PyTorch Distributed (DTensor) operations and custom autograd functions. Access to an NVIDIA H100 or B200 GPU cluster, as the framework relies heavily on its interconnect bandwidth and Transformer Engine acceleration…
Build Personal AI Agents on Windows PCs with New Tools from Microsoft and NVIDIA | NVIDIA Technical Blog
…While cloud frameworks like vLLM are well optimized for multiple GPUs thanks to their use in data centers, PC frameworks like llama.cpp and the ComfyUI implementation in PyTorch are not optimized…